What it means
Using a chat app is one thing. Building AI into your own product or process is another. LLM integration covers the work in between: choosing the model, writing and testing prompts, connecting your data, handling structured outputs, adding tools, controlling cost and monitoring results.
A good integration keeps the model choice in configuration, so you can switch providers or versions without rewriting the product.
Why it matters for a business
The value of AI comes from using it on your own data, inside the tools your team and customers already use. Careful integration is what makes that reliable, secure and affordable over time.
A business example
Things to watch
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Keep prompts, models and settings under version control.
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Validate outputs in code before using them.
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Set cost limits and monitor usage.
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Plan for provider outages with a fallback.